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RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

演示站可以免费使用deepseek-r1满血模型进行AI对话,并支持使用stablediffusion模型画图。本项目是PHP版调用DeepSeek第三方接口进行问答和画图,采用Stream流模式通信,一边生成一边输出。前端采用EventSource,支持Markdown格式解析,支持公式显示,代码有着色处理,支持画图。页面UI简洁,支持上下文连续会话。源码只有几个文件,没用任何框架,支持所有PHP版本,全部开源,极易二开,适合PHP初学者。保姆级教程,账号等周边资源,欢迎进群交流,一切全免费。

Run the full 2.78-trillion-parameter Kimi K3 model, DeepSeek V4.1 Flash or GLM-5.3-Flash beyond available RAM by streaming activated weights directly from NVMe. A dependency-free, embeddable C inference engine.

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Xolotl: run DeepSeek-V4.1-Flash, all 552B, as a local coding agent on one gaming PC (RTX 4090 + 110 GB RAM): ~33 tok/s on agent tasks, ~41 in fast mode, 512K context. Plus GLM-5.3-Flash, Qwen3.8 and LFM3-Omni. MoE experts tiered across VRAM, pinned RAM and NVMe, with Xolotl Direct NVMe->VRAM. OpenAI + Anthropic API.